Dynamics of Maximum Snow Cover Area and Snow Line Altitude Across Nepal (2003-2018) Using Improved MODIS Data

2020 ◽  
Vol 25 (2) ◽  
pp. 17-24
Author(s):  
Nitesh Khadka ◽  
Nitesh Khadka ◽  
Shravan Kumar Ghimire ◽  
Xiaoqing Chen ◽  
Sudeep Thakuri ◽  
...  
Keyword(s):  
Snow Cover ◽  
Monsoon Season ◽  
Temporal Variations ◽  
Vital Role ◽  
Eastern Region ◽  
Snow Cover Area ◽  
Post Monsoon ◽  
Snow Line ◽  
Elevation Zone ◽  
Spatio Temporal

Snow is one of the main components of the cryosphere and plays a vital role in the hydrology and regulating climate. This study presents the dynamics of maximum snow cover area (SCA) and snow line altitude (SLA) across the Western, Central, and Eastern Nepal using improved Moderate Resolution Imaging Spectroradiometer (MODIS; 500 m) data from 2003 to 2018. The results showed a heterogeneous behavior of the spatial and temporal variations of SCA in different months, seasons, and elevation zones across three regions of Nepal. Further, the maximum and minimum SCA was observed in winter (December-February) and post-monsoon (October-November) seasons, respectively. The inter-annual variation of winter SCA showed an overall negative trend of SCA between 2003 to 2018 at the national and regional scales. The SLA was assessed in the post-monsoon season. At the national scale, the SLA lies in an elevation zone of 4500-5000 m, and the approximate SLA of Nepal was 4750 m in 2018. Regionally, the SLA lies in an elevation zone of 4500-5000 m in the Western and Central regions (approx. SLA at 4750 m) and 5000-5500 m in the Eastern region (approx. SLA at 5250 m) in 2018. The SLA fluctuated with the changes in SCA, and the spatio-temporal variations of SLAs were observed in three regions of Nepal. We observed an upward shift of SLA by 33.3 m yr-1 in the Western and Central Nepal and by 66.7 m yr-1 in Eastern Nepal. This study will help to understand the impacts of climate change on snow cover, and the information will be useful for the hydrologist and water resource managers.

scholarly journals A Response of Snow Cover to the Climate in the Northwest Himalaya (NWH) Using Satellite Products

2021 ◽  
Vol 13 (4) ◽  
pp. 655
Author(s):  
Animesh Choudhury ◽  
Avinash Chand Yadav ◽  
Stefania Bonafoni
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Significant Negative Correlation ◽  
Shuttle Radar Topography Mission ◽  
Vital Role ◽  
Snow Cover Area ◽  
Study Region ◽  
Northwest Himalaya ◽  
The Past ◽  
Average Annual Temperature

The Himalayan region is one of the most crucial mountain systems across the globe, which has significant importance in terms of the largest depository of snow and glaciers for fresh water supply, river runoff, hydropower, rich biodiversity, climate, and many more socioeconomic developments. This region directly or indirectly affects millions of lives and their livelihoods but has been considered one of the most climatically sensitive parts of the world. This study investigates the spatiotemporal variation in maximum extent of snow cover area (SCA) and its response to temperature, precipitation, and elevation over the northwest Himalaya (NWH) during 2000–2019. The analysis uses Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra 8-day composite snow Cover product (MOD10A2), MODIS/Terra/V6 daily land surface temperature product (MOD11A1), Climate Hazards Infrared Precipitation with Station data (CHIRPS) precipitation product, and Shuttle Radar Topography Mission (SRTM) DEM product for the investigation. Modified Mann-Kendall (mMK) test and Spearman’s correlation methods were employed to examine the trends and the interrelationships between SCA and climatic parameters. Results indicate a significant increasing trend in annual mean SCA (663.88 km2/year) between 2000 and 2019. The seasonal and monthly analyses were also carried out for the study region. The Zone-wise analysis showed that the lower Himalaya (184.5 km2/year) and the middle Himalaya (232.1 km2/year) revealed significant increasing mean annual SCA trends. In contrast, the upper Himalaya showed no trend during the study period over the NWH region. Statistically significant negative correlation (−0.81) was observed between annual SCA and temperature, whereas a nonsignificant positive correlation (0.47) existed between annual SCA and precipitation in the past 20 years. It was also noticed that the SCA variability over the past 20 years has mainly been driven by temperature, whereas the influence of precipitation has been limited. A decline in average annual temperature (−0.039 °C/year) and a rise in precipitation (24.56 mm/year) was detected over the region. The results indicate that climate plays a vital role in controlling the SCA over the NWH region. The maximum and minimum snow cover frequency (SCF) was observed during the winter (74.42%) and monsoon (46.01%) season, respectively, while the average SCF was recorded to be 59.11% during the study period. Of the SCA, 54.81% had a SCF above 60% and could be considered as the perennial snow. The elevation-based analysis showed that 84% of the upper Himalaya (UH) experienced perennial snow, while the seasonal snow mostly dominated over the lower Himalaya (LH) and the middle Himalaya (MH).

scholarly journals Tropospheric temperature variation over India and links with the Indian summer monsoon : 1971-2000

MAUSAM ◽  
2022 ◽  
Vol 53 (3) ◽  
pp. 289-308
Author(s):  
D. R. KOTHAWALE ◽  
K. RUPA KUMAR
Keyword(s):  
Summer Monsoon ◽  
Southern Oscillation ◽  
Monsoon Season ◽  
Temporal Variations ◽  
Mean Annual Temperature ◽  
Tropospheric Temperature ◽  
Temperature Variations ◽  
Annual Cycles ◽  
The Mean ◽  
Spatio Temporal

In the context of the ever increasing interest in the regional aspects of global warming, understanding the spatio-temporal variations of tropospheric temperature over India is of great importance. The present study, based on the data from 19 well distributed radiosonde stations for the period 1971-2000, examines the seasonal and annual mean temperature variations at the surface and five selected upper levels, viz., 850, 700, 500, 200 and 150 hPa. An attempt has also been made to bring out the association between tropospheric temperature variations over India and the summer monsoon variability, including the role of its major teleconnection parameter, the El Niño/Southern Oscillation (ENSO).   Seasonal and annual mean all-India temperature series are analyzed for surface and five tropospheric levels.  The mean annual cycles of temperature at different tropospheric levels indicate that the pre-monsoon season is slightly warmer than the monsoon season at the surface, 850 hPa and 150 hPa levels, while it is relatively cooler at all intermediate levels.  The mean annual temperature shows a warming of 0.18° C and 0.3° C per 10 years at the surface and 850 hPa, respectively.   Tropospheric temperature anomaly composites of excess (deficient) monsoon rainfall years show pronounced positive (negative) anomalies during the month of May, at all the levels.  The pre-monsoon pressure of Darwin has significant positive correlation with the monsoon temperature at the surface and 850 hPa.

Revealing snow cover dynamics in the Hindu Kush Himalaya over the past decades

2020 ◽  
Author(s):  
Kathrin Naegeli ◽  
Carlo Marin ◽  
Valentina Premier ◽  
Gabriele Schwaizer ◽  
Martin Stengel ◽  
...  
Keyword(s):  
High Resolution ◽  
Snow Cover ◽  
Satellite Data ◽  
Weather Forecast ◽  
Short Wave ◽  
Climate Modelling ◽  
Snow Cover Area ◽  
Hindu Kush ◽  
Spatio Temporal ◽  
Area Percentage

<p>Knowledge about the snow cover distribution is of high importance for climate studies, weather forecast, hydrological investigations, irrigation or tourism, respectively. The Hindu Kush Himalayan (HKH) region covers almost 3.5 million km<sup>2</sup> and extends over eight different countries. The region is known as ‘water tower’ as it contains the largest volume of ice and snow outside of the polar ice sheets and it is the source of Asia’s largest rivers. These rivers provide ecosystem services, the basis for livelihoods and most importantly living water for drinking, irrigation, energy production and industry for two billion people, a fourth of the world’s population, living in the mountains and downstream.</p><p>The spatio-temporal variability of snow cover in the HKH is high and studies reported average snow-covered area percentage of 10–18%, with greater variability in winter (21–42%) than in summer (2–4%). However, no study systematically investigated snow cover metrics, such as snow cover area percentage (SCA), snow cover duration (SCD) or snow cover onset (SCOD) and melt-out day (SCMD), for the entire region so far. Here, we thus present unique in-sights of regional and sub-regional snow cover dynamics for the HKH based on almost four decades, an exceptionally long and in view of the climate modelling community valuable timeseries, of satellite data obtained within the ESA CCI+ Snow project.</p><p>Our results are based on Advanced Very High Resolution Radiometer (AVHRR) data, collected onboard the polar orbiting satellites NOAA-7 to -19, providing daily, global imagery at a spatial resolution of 5 km. Calibrated and geocoded reflectance data and a consistent cloud mask pre-processed and provided by the ESA Cloud_cci project as global 0.05° composites are used. The retrieval of snow extent considers the high reflectance of snow in the visible spectra and the low reflectance values in the short-wave infrared expressed in the Normalized Difference Snow Index (NDSI). Additional thresholds related to topography and land cover are included to derive the fractional snow cover of every pixel. A temporal gap-filling was applied to mitigate the influence of clouds. Reference snow maps from high-resolution optical satellite data as well as in-situ station data were used to validate the time series.</p>

Mortality Pattern of Broiler Rabbits in an Organized Farm in Bihar, India

2020 ◽  
Author(s):  
Asit Chakrabarti
Keyword(s):  
Monsoon Season ◽  
Abdominal Cavity ◽  
Winter Season ◽  
The Other ◽  
Housing System ◽  
Pathological Examination ◽  
Eastern Region ◽  
Mortality Pattern ◽  
Bacterial Diseases ◽  
Post Monsoon

Background: The pre and post-weaning mortality in broiler rabbit limits the production potential and lower the income generation through rabbit farming. Therefore, mortality pattern of animals in a farm is very essential clue for future strategy to combat the incidences of various diseases and prevention. Considering the above fact the present study was undertaken to find out the incidences of various rabbit diseases and mortality in an organized institutional farm.Methods: ICAR Research Complex for Eastern Region, Patna was maintaining a broiler rabbit farm with 364 rabbit comprising Newzealand White (194) and Soviet Chinchilla (170) rabbit breed. During the three years (October, 2011 to September, 2014) study period in total 364 rabbits were under observation. The seasonal variation viz. (pre-monsoon, monsoon, post-monsoon and winter, in regards to mortality, disease incidences, young and adults, sex variation, breed, housing system etc were recorded. The incidences of disease and mortality of rabbits were diagnosed through pathological examination and postmortem findings. The descriptive statistics and ÷2 test were used to explain the statistical significance.Result: During the three years study period out of 364 broiler rabbits (Soviet Chinchilla and Newzealand white) in total 63 rabbits (17.31%) were died due to various diseases. The coccidiosis (3.02%), green slime disease (2.20%), haemorrhagic tracheitis (1.92%), enteritis (1.65%), pneumonia (1.37%) and peritonitis (1.37%) were affected more than the other diseases. Apart from these the other ailments that affected broiler rabbits were ear cancer (0.82%), gastroenteritis (0.82%), stomach infection (0.82%), cardinogenic shock (0.55%), stomach impaction (0.55%), kidney infection (0.55%), limb injury (0.27%), ascites (0.27%), cystitis (0.27%), abscess in abdominal cavity (0.27%), rupture of liver and gall bladder (0.27%) as well as injury of eye and blindness (0.27%). The Soviet Chinchilla rabbits were less (7.14%) affected than the Newzealand white (10.16%). It was observed that mortality of male rabbits (6.04%) were less than the female rabbits (11.26%) and mortality of young were higher (11.54%) than the adult rabbits (5.77%). The seasonal variations in mortality of broiler rabbits were observed in present study. In monsoon season mortality was maximum i.e. 6.32% whereas, in post-monsoon it was 5.49%, pre-monsoon 3.02% and in winter season mortality was only 2.47%. The Soviet Chinchilla rabbits were less susceptible and comparatively better performer in regards to disease resistance. It may be concluded that in broiler rabbit farm coccidiosia is a major concern along with other parasitic and bacterial diseases. However, proper hygiene and sanitation along with periodic treatment with coccidiostat and deworming reduces mortality of rabbits. 

scholarly journals Variability of snow line elevation, snow cover area and depletion in the main Slovak basins in winters 2001–2014

2016 ◽  
Vol 64 (1) ◽  
pp. 12-22 ◽  
Author(s):  
Pavel Krajčí ◽  
Ladislav Holko ◽  
Juraj Parajka
Keyword(s):  
Snow Cover ◽  
Winter Season ◽  
High Mountain ◽  
Spatial And Temporal Variability ◽  
Considerable Variability ◽  
Snow Cover Area ◽  
The Third ◽  
Snow Line ◽  
Maximum Elevation ◽  
Basin Elevation

Abstract Spatial and temporal variability of snow line (SL) elevation, snow cover area (SCA) and depletion (SCD) in winters 2001–2014 is investigated in ten main Slovak river basins (the Western Carpathians). Daily satellite snow cover maps from MODIS Terra (MOD10A1, V005) and Aqua (MYD10A1, V005) with resolution 500 m are used. The results indicate three groups of basins with similar variability in the SL elevation. The first includes basins with maximum elevations above 1500 m a.s.l. (Poprad, Upper Váh, Hron, Hornád). Winter median SL is equal or close to minimum basin elevation in snow rich winters in these basins. Even in snow poor winters is SL close to the basin mean. Second group consists of mid-altitude basins with maximum elevation around 1000 m a.s.l. (Slaná, Ipeľ, Nitra, Bodrog). Median SL varies between 150 and 550 m a.s.l. in January and February, which represents approximately 40–80% snow coverage. Median SL is near the maximum basin elevation during the snow poor winters. This means that basins are in such winters snow free approximately 50% of days in January and February. The third group includes the Rudava/Myjava and Lower Váh/Danube. These basins have their maximum altitude less than 700 m a.s.l. and only a small part of these basins is covered with snow even during the snow rich winters. The evaluation of SCA shows that snow cover typically starts in December and last to February. In the highest basins (Poprad, Upper Váh), the snow season sometimes tends to start earlier (November) and lasts to March/April. The median of SCA is, however, less than 10% in these months. The median SCA of entire winter season is above 70% in the highest basins (Poprad, Upper Váh, Hron), ranges between 30–60% in the mid-altitude basins (Hornád, Slaná, Ipeľ, Nitra, Bodrog) and is less than 1% in the Myjava/Rudava and Lower Váh/Danube basins. However, there is a considerable variability in seasonal coverage between the years. Our results indicate that there is no significant trend in mean SCA in the period 2001–2014, but periods with larger and smaller SCA exist. Winters in the period 2002–2006 have noticeably larger mean SCA than those in the period 2007–2012. Snow depletion curves (SDC) do not have a simple evolution in most winters. The snowmelt tends to start between early February and the end of March. The snowmelt lasts between 8 and 15 days on average in lowland and high mountain basins, respectively. Interestingly, the variability in SDC between the winters is much larger than between the basins.

scholarly journals SPATIO-TEMPORAL CHANGE IN SNOW COVER AREA USING RS & GIS IN THE GORI GANGA WATERSHED, KUMAUN HIGHER HIMALAYA

2021 ◽  
Vol 9 (03) ◽  
pp. 30-34
Author(s):  
D.S. Parihar ◽  
◽  
J.S. Rawat ◽  
Keyword(s):  
Global Warming ◽  
Snow Cover ◽  
Temporal Change ◽  
Average Rate ◽  
Landsat Tm ◽  
Snow Cover Area ◽  
Time Periods ◽  
Spatio Temporal ◽  
Normalized Difference Snow Index ◽  
Landsat Satellite

Present research paper is an attempt to examine the dynamics of snow cover by using Normalized Difference Snow Index (NDSI) in Gori Ganga watershed, Kumaun Himalaya, Uttarakhand (India). For the study of snow cover of Landsat satellite imageries of three different time periods like Landsat TM of 1990, Landsat TM of 1999 and Landsat TM 2016 were used. Geographical distribution of snow cover reveals that in 1990 about 30.97% (678.87 km2), in 1999 about 25.77% (564.92 km2) area of the Gori Ganga watershed was under snow cover while in 2016 the snow cover was found only 15.08% (330.44 km2). These data suggest that due to global warming about 348.43 km2 snow cover of Gori Ganga watershed has been converted into non-snow cover area at an average rate 13.40 km2/year during the last 26 years.

Snow Cover Dynamics and its Spatio-Temporal Distribution in the Central Higher Himalaya of India

2021 ◽  
Vol 14 (9) ◽  
pp. 15-22
Author(s):  
Masoom Reza ◽  
Ramesh Chandra Joshi
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Geographical Area ◽  
Temporal Distribution ◽  
Melting Rate ◽  
Optical Data ◽  
Snow Cover Area ◽  
Central Himalayas ◽  
Spatio Temporal ◽  
The Impact

Retreating glaciers, changing timber line and decreasing accumulation of snow in the Himalaya are considered the indicators of climate change. In this study, an attempt is made to observe the snow cover change in the higher reaches of the Central Himalayas. Investigation of climate change through snow cover is very important to understand the impact and adaptation in an area. Landsat thematic and multi spectral optical data with a spatial resolution of 60m and 30m are considered for the estimation and extraction of snow cover. Total 3,369 Km2 snow cover area is lost since 1972 out of total geographical area i.e. 17,227 Km2. The accumulation of snow during winter is lower than the melting rate during summer. The current study identified the decrease of 19.6 % snow cover in 47 years since 1972 to 2019. Composite satellite imageries of September to December show that the major part of the study area covered with snow lies above 3600m. Overall observation indicates that in 47 years, permanent snow cover is decreasing in Central Himalayas.

scholarly journals Spatial Variations in the Diurnal Pattern of Precipitation over Nepal Himalayas

2015 ◽  
Vol 15 (2) ◽  
pp. 57-64 ◽  
Author(s):  
Dibas Shrestha ◽  
Rashila Deshar
Keyword(s):  
Summer Monsoon ◽  
Diurnal Cycle ◽  
Monsoon Season ◽  
Tropical Rainfall Measuring Mission ◽  
Early Morning ◽  
Temporal Variations ◽  
Diurnal Cycles ◽  
Diurnal Cycle Of Precipitation ◽  
Spatio Temporal ◽  
The Impact

The Central Himalayan Region (Nepal Himalayas), comprised of two clear sub-parallel mountain ranges, is atypical location for studying the impact of rugged topography on spatio temporal variations of precipitation. The relationship between topography and diurnal cycles of rainfall have been investigated utilizing 13-year (1998–2010) high resolution (0.05° × 0.05°) Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data. An investigation of diurnal cycle of precipitation revealed an afternoon maximum during the pre-monsoon season (March–May) and midnight–early morning maximum during the summer monsoon season (June–August)over the southern slopes of the Himalayas. The summer monsoon exhibited a robust spatial variation of diurnal cycle of precipitation, during afternoon-evening time, primary rainfall peak appeared along the Lesser Himalayas (~2,000–2,200 m above mean sea level), while early-morning rain in contrast showed maximum concentration along the southern margin of the Himalayas (~500–700 m above MSL). An afternoon-evening rainfall peak was attributed to higher rain frequency, whereas early-morning rainfall peak was attributed to fewer but rather intense rainfall. It is suggested that, confluence between down slope and moist south easterly monsoon flow triggers convection near the foothills of the Himalayas during early morning period. The results further suggested the morning precipitation moves southward in the mature monsoon season.DOI: http://dx.doi.org/njst.v15i2.12116Nepal Journal of Science and Technology Vol. 15, No.2 (2014), 57-64

scholarly journals Spatio-temporal variations in water quality, hydrochemistry and its controlling factors in a perennial river in India

2021 ◽  
Vol 11 (11) ◽  
Author(s):  
Raj Setia ◽  
Shaveta Lamba ◽  
Shard Chander ◽  
Vinod Kumar ◽  
Randhir Singh ◽  
...  
Keyword(s):  
Water Quality ◽  
River Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Temporal Variations ◽  
Post Monsoon ◽  
Drinking And Irrigation ◽  
Poor Water Quality ◽  
Spatio Temporal ◽  
The One

AbstractThe spatial and temporal variations in the hydrochemistry of the Sutlej river in the Indian Punjab were studied based on water quality parameters analysed during pre- and post-monsoon seasons of the years 2017 and 2018. The grab water samples were collected from the river using stratified random sampling and analysed for pH, electrical conductivity (EC), carbonate (CO3−2), bicarbonate (HCO3−), chloride (Cl−), nitrate (NO3−), total hardness, calcium (Ca+2), sodium (Na+) and potassium (K+) using standard methods. Spatio-temporal variations in the parameters used to evaluate the water quality for irrigation (electrical conductivity (EC), residual sodium carbonate (RSC) and sodium absorption ratio (SAR)) were also studied. In order to rate the composite influence of all the physicochemical parameters, water quality index (WQI) was computed. Spatial variations in WQI for drinking and irrigation purposes were studied using the inverse distance weighted method in GIS. Results showed that the river water was alkaline in nature, HCO3− and Cl− are the major anions, and Ca2+ and Na+ are the cations in the river water during both seasons. The regression analysis of EC with cations and anions showed that the regression coefficient was mainly significant with Ca2+ and HCO3−, irrespective of the season. The concentration of ions was not significantly affected by season, but it was higher along transboundary of the river. Total alkalinity of water was significantly (p < 0.05) higher during pre-monsoon than post-monsoon season. The EC, SAR and RSC values during different seasons showed that  > 85% of the water samples were in good categories for irrigation purposes. According to grades of WQI for drinking purposes, the poor WQI was observed in 3.6%, 3.7% and 5.9% of the samples during pre-2017, pre-2018 and post-monsoon 2018, respectively. The poor water quality index for irrigation purposes was observed in 16.7% and 4.7% of the samples during pre-monsoon 2017 and 2018, respectively. The water quality index values for drinking and irrigation were higher (poor water quality) along transboundary of the river. The ratio of Ca2+/Mg2+, (Na+ + K+)/TZ+ and Ca2+ + Mg2+/(Na+ + K+) indicated both carbonate and silicate lithology contribute to hydrochemistry of the river besides anthropogenic factors. Non-metric multidimensional scaling showed that all the samples are of a similar origin across the river including transboundary, whereas cluster analysis resulted in the two main groups: pH and Cl in the one group, and EC along with the remaining cations and anions in the other group during pre-monsoon, but pH in the one group, and EC along with the remaining cations and anions in the other group during post-monsoon. The high concentration of Cl− is a signature of anthropogenic inputs in addition to the contribution of natural factors. These results suggest that the cultivation of crops on the soils along transboundary may cause the transfer of ions through the food chain to human beings affecting their health. Moreover, drinking of river water by inhabitants living along transboundary may affect their health.

scholarly journals Spatio-temporal variation analysis of snow cover in China-Pakistan Economic Corridor based on remote sensing technology

2021 ◽  
Vol 237 ◽  
pp. 01018
Author(s):  
Fan Zhang ◽  
ZhiHua Zhang
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Annual Variation ◽  
Low Frequency ◽  
Snow Cover Area ◽  
Remote Sensing Technology ◽  
Maximum Value ◽  
Sensing Technology ◽  
Spatio Temporal ◽  
Karakoram Mountains

Based on the MODIS10A2 snow product data from 2001 to 2019, the characteristics of annual variation, interannual variation and spatial distribution of snow cover in China Pakistan Economic Corridor from 2001 to 2019 are analyzed by using remote sensing technology. The result shows that: the snow-cover in a year generally starts from the middle of October, and the snow cover area reaches the maximum value in January of the next year, and reaches the minimum value in July. From 2001 to 2019, the snow area of China-Pakistan Economic Corridor generally showed a decreasing trend. The distribution of snow in the China-Pakistan Economic Corridor is extremely uneven. The northern area is obviously more than that in the south. The mountainous and plateau areas are with high frequency of snow cover, and the plains are areas with low frequency of snow-cover. Permanent snow-cover is relatively low. Few, mainly concentrated in the Karakoram Mountains, in terms of distribution range, mainly distributed in 4452-8378 m.

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